Meta Llama

Meta Llama is the leading open-weight large language model family, offering frontier-class performance that you can run on your own infrastructure with full control over data privacy, customization, and deployment costs. Llama models are released under permissive licenses that allow commercial use.

Key use cases include:

• Self-hosted chatbots and assistants for data-sensitive environments
• Fine-tuning on domain-specific data for specialized applications
• Research and experimentation with full model transparency
• Cost-effective inference at scale — no per-token API fees
• On-device and edge deployments with smaller Llama variants
• Building custom model variants with LoRA and QLoRA fine-tuning

Llama is used by teams who need full control over their AI stack — from startups avoiding vendor lock-in to enterprises with strict data residency requirements. The Llama 3.1 405B model competes with GPT-4-class models, while smaller variants (8B, 70B) offer excellent performance-to-cost ratios.

The extensive open-source ecosystem around Llama (vLLM, Ollama, llama.cpp, Hugging Face) makes it accessible whether you are running on a laptop or a GPU cluster.

1. Accept the license at llama.meta.com or download directly from Hugging Face.
2. For local inference, install a runtime:

   # Ollama (easiest)
   curl -fsSL https://ollama.ai/install.sh | sh
   ollama run llama3.1
   
   # Or with vLLM (production serving)
   pip install vllm
   python -m vllm.entrypoints.openai.api_server \
     --model meta-llama/Llama-3.1-8B-Instruct

3. For hosted API access without managing infrastructure, use providers like Together AI, Groq, or Replicate.

Pricing: Model weights are free to download. Self-hosting costs depend on GPU infrastructure. Hosted APIs typically charge $0.05-0.20/1M tokens for 8B, and $0.60-1.00/1M tokens for 70B models.